1. Technical Field
The present disclosure relates to the field of information search. Particularly, the present disclosure relates to the field of visual search.
2. Description of the Related Art
The use of mobile devices, such as cellular phones or personal digital assistant (PDA) devices has increased exponentially in the last decade. Often, such mobile devices include a camera and a display screen for displaying images at which the camera is pointed. Since people often carry their camera-enabled mobile devices with them, it would be beneficial to provide additional mobile applications for utilizing the camera and display capabilities of such prevalent mobile devices.
In a typical mobile visual search application, a query image is matched with a set of images in a repository and the metadata associated with the matched repository image is presented to the user. A typical application is to click a photo (query image) using a Smartphone and transmit it to a central server where an image-based search is carried out to identify matching images from a repository and the relevant information about the query image is presented to the user.
Several algorithms are available for image matching using local features and/or global features of a query image. For certain applications which involve capturing an image of a part of a newspaper magazine, considering the captured image as query image and retrieving information about the query image, one of the main challenges is to tackle the textual information surrounding the actual region of interest in the captured image.
Typically, textual information has a sharp contrast compared to its background and hence produces a large number of local features, e.g. when using the SIFT technique, many keypoints lie around the textual information. If a plurality of images stored in the repository, and a query image comprising text distracters are treated as regular images, to find out a match between the respective feature descriptors, certain characters of the textual information present in the query image may match with certain characters present in an image(s) stored in the repository. Thus a decision solely based on such feature matches may indeed turn out to be inappropriate. Such inappropriate matches are called false positives. It is observed that incase of typical image matching applications, approximately 40% of false positives are created due to the presence of text distracters.
Hence there was felt a need for a method that improves the image matching accuracy despite the presence of text distracters. There was also felt a need for a method and system that finds a near perfect match, effectively and efficiently, for the query image amongst the repository images.
The above mentioned shortcomings, disadvantages and problems are addressed herein and which will be understood by reading and studying the following specification.